code-review

---
name: code-review
description: |-
  Review the current diff, or a PR number/branch/path target, for correctness bugs (plus reuse/simplification/efficiency cleanups where the model's review recipe covers them) at the given effort level (low|medium|high|xhigh|max: from few high-confidence findings up to many, some of them uncertain; ultra: deep multi-agent review in the cloud); with no level given, it reuses the level you typed last. Pass --comment to post findings as inline PR comments, or --fix to apply the findings to the working tree after the review. Pass --max-findings <n> to report up to n findings, or --max-findings all for every finding. The choice stays until you pass --max-findings default. For ultra on a GitHub.com PR target, --post asks to post the finished review’s findings to the PR as a single comment from the user’s GitHub account (not a review; the launch dialog still confirms in interactive sessions, while non-interactive mode posts on the flag alone) and --no-post hides that option.
---

`high effort → 8 inline angles → dedup (no verify) → ≤10 findings`

You are reviewing for **recall** at high effort: catch every real bug a careful
reviewer would catch in one sitting. At this level, catching real bugs matters
more than avoiding false positives. Err on the side of surfacing.

## Phase 0 — Gather the diff

Run `git diff @{upstream}...HEAD` (or `git diff main...HEAD` / `git diff HEAD~1`
if there's no upstream) to get the unified diff under review. If there are
uncommitted changes, or the range diff is empty, also run `git diff HEAD` and
include the working-tree changes in scope — the review often runs before the
commit. If a PR number, branch name, or file path was passed as an argument,
review that target instead. Treat this diff as the review scope.

## Phase 1 — Find candidates (3 correctness angles + 3 cleanup angles + 1 altitude angle + 1 conventions angle, up to 6 each)

Run **8 independent finder angles** in sequence yourself, in THIS context — do NOT spawn subagents for them. Each
surfaces **up to 6 candidate findings** with `file`, `line`, a one-line
`summary`, and a concrete `failure_scenario`.

### Angle A — line-by-line diff scan

Read every hunk in the diff, line by line. Then Read the enclosing function for
each hunk — bugs in unchanged lines of a touched function are in scope (the PR
re-exposes or fails to fix them). For every line ask: what input, state, timing,
or platform makes this line wrong? Look for inverted/wrong conditions,
off-by-one, null/undefined deref, missing `await`, falsy-zero checks,
wrong-variable copy-paste, error swallowed in catch, unescaped regex metachars.

### Angle B — removed-behavior auditor

For every line the diff DELETES or replaces, name the invariant or behavior it
enforced, then search the new code for where that invariant is re-established.
If you can't find it, that's a candidate: a removed guard, a dropped error
path, a narrowed validation, a deleted test that was covering a real case.

### Angle C — cross-file tracer

For each function the diff changes, find its callers (Grep for the symbol) and
check whether the change breaks any call site: a new precondition, a changed
return shape, a new exception, a timing/ordering dependency. Also check callees:
does a parallel change in the same PR make a call unsafe?

### Reuse

The angles above hunt for bugs; this one and the next two hunt for cleanup in
the changed code. Flag new code that re-implements something the codebase
already has — Grep shared/utility modules and files adjacent to the change,
and name the existing helper to call instead.

### Simplification

Flag unnecessary complexity the diff adds: redundant or derivable state,
copy-paste with slight variation, deep nesting, dead code left behind. Name
the simpler form that does the same job.

### Efficiency

Flag wasted work the diff introduces: redundant computation or repeated I/O,
independent operations run sequentially, blocking work added to startup or
hot paths. Also flag long-lived objects built from closures or captured
environments — they keep the entire enclosing scope alive for the object's
lifetime (a memory leak when that scope holds large values); prefer a
class/struct that copies only the fields it needs. Name the cheaper
alternative.

### Altitude

Check that each change fixes the root cause at the right depth rather than
patching a symptom with a fragile bandaid. Special cases layered on shared
infrastructure are a sign the fix isn't deep enough — prefer the simpler, more
general change to the underlying mechanism over adding special cases, and name
that change.

### Conventions (CLAUDE.md)

Find the CLAUDE.md files that govern the changed code: the user-level
~/.claude/CLAUDE.md, the repo-root CLAUDE.md, plus any CLAUDE.md or
CLAUDE.local.md in a directory that is an ancestor of a changed file (a
directory's CLAUDE.md only applies to files at or below it). Read each one
that exists, then check the diff for clear violations of the rules they state.

Only flag a violation when you can quote the exact rule and the exact line
that breaks it — no style preferences, no vague "spirit of the doc"
inferences. In the finding, name the CLAUDE.md path and quote the rule so the
report can cite it. If no CLAUDE.md applies, return nothing for this angle.

Cleanup, altitude, and conventions candidates use the same
`file`/`line`/`summary` shape; in `failure_scenario`, state the concrete
cost (what is duplicated, wasted, harder to maintain, or which CLAUDE.md rule
is broken) instead of a crash. Correctness bugs always outrank cleanup,
altitude, and conventions findings when the output cap forces a cut.

Pass every candidate with a nameable failure scenario through — finders that
silently drop half-believed candidates are the dominant cause of misses.

## Phase 2 — Dedup only (no verify)

Pool all candidates. Dedup near-duplicates only (same defect, same location, same reason → keep one). Do NOT run verifiers; do NOT re-judge. Sort by severity.

## Output

Target **at least 5 findings**. If fewer genuine findings exist, emit what you have — do not invent to hit the floor.

Return findings as a JSON array of at most 10 objects:

```json
[
  {
    "file": "path/to/file.ext",
    "line": 123,
    "summary": "one-sentence statement of the bug",
    "failure_scenario": "concrete inputs/state → wrong output/crash"
  }
]
```

Ranked most-severe first. If more than 10 survive, keep the 10 most
severe. If nothing survives, return `[]`. Do not call the
ReportFindings tool even if it is available - this review's
output contract is the JSON block above.

• SKILL.md 7 KB
• high.md 6 KB
• low.md 1 KB
• max.md 8 KB
• medium.md 2 KB
• report-findings-tool.md 3 KB
• xhigh.md 7 KB